Abstract
This paper deals with identifying if a tumor present in the lung is benign, unsure, or malignant using Deep Learning concepts on a dataset with CT, PET scans of the lungs of patients. The graveness of a tumor is highly dependent on the intrinsic ordinal relationship of the nodules in the lung at various stages- by stages, those are benign, unsure, or malignant. Our focus through this study is to work around detecting the type of tumor and improve the efficiency in identifying unsure or pre-malignant tumors using VGG-16 neural frameworks on the LIDC-IDRI dataset.
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Angeline, R., Kanna, S.N., Menon, N.G., Ashwath, B. (2022). Identifying Malignancy of Lung Cancer Using Deep Learning Concepts. In: Garg, L., Basterrech, S., Banerjee, C., Sharma, T.K. (eds) Artificial Intelligence in Healthcare. Advanced Technologies and Societal Change. Springer, Singapore. https://doi.org/10.1007/978-981-16-6265-2_3
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